1. Field of the Invention
The present invention relates to an information processing apparatus and an information processing method. In particular, the present invention relates to a technique which is suitable for measuring a position and orientation of an object whose three-dimensional shape is known.
2. Description of the Related Art
Recently, complex tasks such as assemblage of industrial products which have been manually performed are being performed by robots instead. When the robot assembles such industrial products, the robot holds a component by an end effecter, e.g., a hand, so that it becomes necessary to accurately measure a relative position and orientation between the component and the robot (i.e., robot hand).
There is a technique for accurately estimating the position and orientation of an object using, at the same time, a two-dimensional image (i.e., an intensity image or a color image) acquired by a camera and a range image acquired by a range sensor. Such a technique for accurately measuring the position and orientation of the object is discussed in [Y. Hel-Or and M. Werman, “Pose estimation by fusing noisy data of different dimensions”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No. 2, pp. 195-201, 1995]. The above-described literature discusses treating a feature in the two-dimensional image as a three-dimensional point in which a depth is uncertain, with respect to the two-dimensional images and the range images which are input in time-series. The position and orientation of the object is then updated using a Kalman filter so that an error between the feature in the two-dimensional image and a three-dimensional model and an error between the three-dimensional point in the range image and the three-dimensional model are minimized.
The conventional technique for estimating the position and orientation of the object using the two-dimensional image and the range image assumes that an imaging apparatus freely moves. Estimation is thus performed assuming that a relative geometric relation between pieces of measurement data which are input in time-series is unknown. As a result, if the imaging apparatus is to greatly move between times for capturing the images, stability is lost, or estimation accuracy is lowered.
On the other hand, there are cases where the object is to be measured by mounting the imaging apparatus on a robot arm and moving the imaging apparatus, or a fixed imaging apparatus is to measure the object which is held by the robot arm and moved. In such cases, motion information of the robot can be referred to as the information for observing the movement of the imaging apparatus or the measuring object between image capturing times.
The motion information of the robot includes error factors such as an error originating in repetitive accuracy in controlling the robot and an error originating in calibration accuracy. Nevertheless, the motion information is highly accurate and useful information to be used in estimating the position and orientation. However, according to the conventional technique, robot motion cannot be effectively used as the observation information even if the motion information of the robot can be acquired.
Further, Japanese Patent Application Laid-Open No. 2005-201824 discuses a known technique referred to as motion stereo which simply uses the motion information. Such a technique estimates the position and orientation by adding, to an approximate position and orientation, a difference in the position and orientation acquired from the motion information.
However, as described above, the robot motion information includes a predetermined amount of ambiguity. It is thus desirable to update the position and orientation while considering the ambiguity.